Configurations are disclosed for a health system to be used in various healthcare applications, e.g., for patient diagnostics, monitoring, and/or therapy. The health system may comprise a light generation module to transmit light or an image to a user, one or more sensors to detect a physiological parameter of the user's body, including their eyes, and processing circuitry to analyze an input received in response to the presented images to determine one or more health conditions or defects.

Systems and methods for assessing a cardiac arrhythmia risk of a patient, such as a risk for developing atrial fibrillation, are disclosed. An exemplary medical-device system includes an arrhythmia predictor circuit configured to receive physiologic information of a patient, and in an absence of atrial tachyarrhythmia in the patient, determine a risk of the patient developing future atrial tachyarrhythmia using the physiologic information. In accordance with the arrhythmia risk indication, the system can generate an alert, or initiate more aggressive monitoring of a patient identified as having a high atrial tachyarrhythmia risk.

An ECG processing system for identifying noisy ECG data segments is provided. The ECG processing system includes a network interface and a processor. The network interface is configured to receive a first collection of ECG data segments from wearable medical devices associated with a plurality of patients, each wearable medical device of the wearable medical devices being configured to be continuously worn by a patient for an extended period of time. The processor is configured to produce a second collection of ECG data segments from the first collection of ECG data segments that excludes noisy ECG data segments.

Disclosed is a method for computerizing delineation and/or multi-label classification of an ECG signal, including: applying a neural network to the ECG, labelling the ECG, and optionally displaying the labels according to time with the ECG signal.

The present disclosure relates to a wearable monitor device and methods and systems for using such a device. In certain embodiments, the wearable monitor records cardiac data from a mammal and extracts particular features of interest. These features are then transmitted and used to provide health-related information about the mammal.

A method of modelling and extracting information from a photoplethysmography, PPG, signal comprises decomposing and modelling (102) the PPG signal as a long-term periodic component and a short-term periodic component. The method further comprises summarizing (104) the information contained in the PPG signal, based on a distribution of fitted parameters of the modelled long-term and short-term periodic components.

Systems and techniques for managing biological signals. In one implementation, a method includes receiving a cardiac biological signal that includes information describing events, determining a merit of each event based on one or more of a severity of a cardiac condition associated with the event and a quality of the event, and handling a subset of the events that meet a merit criterion. The subset can be handled for medical purposes.

An IMD system receives a near field His bundle electrical signal produced by a patient's heart via a first sensing electrode vector and a far field cardiac electrical signal via a second sensing electrode vector different than the first sensing electrode vector. The IMD system generates His bundle pacing pulses delivered to the patient's heart via a His pacing electrode vector and determines a type of cardiac capture evoked by a His bundle pacing pulse.

Configurations are disclosed for a health system to be used in various healthcare applications, e.g., for patient diagnostics, monitoring, and/or therapy. The health system may comprise a light generation module to transmit light or an image to a user, one or more sensors to detect a physiological parameter of the user's body, including their eyes, and processing circuitry to analyze an input received in response to the presented images to determine one or more health conditions or defects.

Disclosed herein are devices, systems, methods and platforms for continuously monitoring the health status of a user, for example the cardiac health status. The present disclosure describes systems, methods, devices, software, and platforms for continuously monitoring a user's low-fidelity health-indicator data (for example and without limitation PPG signals, heart rate or blood pressure) from a user-device in combination with corresponding (in time) data related to factors that may impact the health-indicator (other-factors) to determine whether a user has normal health as judged by or compared to, for example and not by way of limitation, either (i) a group of individuals impacted by similar other-factors, or (ii) the user him/herself impacted by similar other-factors.